Flash floods are often responsible for deaths and damage to infrastructure. The objective of this work is to create a data-driven model to understand how predisposing factors influence the spatial variation of the triggering factor (rainfall intensity) in the case of flash floods in the continental area of Portugal. Flash floods occurrences were extracted from the DISASTER database. We extracted the accumulated precipitation from the Copernicus database by considering two days of duration. The analysed predisposing factors for flooding were extracted considering the whole basin where each occurrence is located. These factors include the basin area, the predominant lithology, drainage density, and the mean or median values of elevation, slope, stream power index (SPI), topographic wetness index (TWI), roughness, and four soil properties. The Random Forest algorithm was used to build the models and obtained mean absolute percentage error (MAPE) around 19%, an acceptable value for the objectives of the work. The median of SPI, mean elevation and the area of the basin are the top three most relevant predisposing factors interpreted by the model for defining the rainfall input for flash flooding in mainland Portugal.

Gunung Bromo Education Forest is a forest that functions as a buffer area to maintain the balance of the surrounding area. However, the undulating to hilly topography, the presence of rivers, and land management for annual crops can make the area vulnerable to erosion-induced degradation. This research aims to analyze and classify the erosion hazard level in Gunung Bromo Education Forest and analyze the relationship between research parameters and erosion in Gunung Bromo Education Forest. Erosion was predicted using the MUSLE method. This research used an explorative-descriptive method incorporating a survey and laboratory analysis. Furthermore, data analysis used was Analysis of Variance (ANOVA), Duncan's Multiple Range Test (DMRT) at a 5% significance level, and Pearson correlation test. The results showed that Gunung Bromo Education Forest erosion ranged from 0.025 to 78.36 t ha(-1)y(-1). The erosion hazard level in Gunung Bromo Education Forest is in the very light to heavy class and is dominated by the light class. The factors of erosivity (R), erodibility (K), slope (LS), and crop management (C) are positively correlated with erosion values. The conservation factor (P) is negatively correlated with erosion values. Making remedial efforts according to the erosion hazard level is important to avoid greater damage.

Forests are increasingly impacted by climate change, affecting tree growth and carbon sequestration. Tree-ring width, closely related to tree growth, is a key climate proxy, yet models describing ring width or growth often lack comprehensive environmental data. This study assesses ERA5-Land data for tree-ring width prediction compared to automatic weather station observations, emphasizing the value of extended and global climate data. We analyzed 723 site-averaged and detrended tree-ring chronologies from two broadleaved and two gymnosperm species across Europe, integrating them with ERA5-Land climate data, CO2 concentration, and a drought index (SPEI12). A subset was compared with weather station data. For modelling interannual variations of tree-ring width we used linear models to assess parameter importance. ERA5-Land and weather-station-based models performed similarly, maintaining stable correlations and consistent errors. Models based on meteorological data from weather stations highlighted SPEI12, sunshine duration, and temperature extremes, while ERA5-Land models emphasized SPEI12, dew-point temperature (humidity), and total precipitation. CO2 positively influenced the growth of gymnosperm species. ERA5-Land facilitated broader spatial analysis and incorporated additional factors like evaporation, snow cover, and soil moisture. Monthly assessments revealed the importance of parameters for each species. Our findings confirm that ERA5-Land is a reliable alternative for modeling tree growth, offering new insights into climate-vegetation interactions. The ready availability of underutilized parameters, such as air humidity, soil moisture and temperature, and runoff, enables their inclusion in future growth models. Using ERA5-Land can therefore deepen our understanding of forest responses to diverse environmental drivers on a global scale.

Tree destruction induced by heavy rainfall, an overlooked type of forest degradation, has been exacerbated along with global climate change. On the Chinese Loess Plateau, especially in afforested gully catchments dominated by Robinia pseudoacacia, destructive rainfall events have increasingly led to widespread forest damage. Previous study has manifested the severity of heavy rainfall-induced tree destruction and its association with topographic change, yet the contributions of tree structure and forest structure remain poorly understood. In this study, we quantified the destroyed trees induced by heavy rainfall using light detection and ranging (LiDAR) techniques. We assessed the influence of tree structure (tree height, crown diameter, and crown area), forest structure (tree density, gap fraction, leaf area index, and canopy cover), and terrain parameters (elevation, slope, and terrain relief) using machine learning models (random forest and logistic regression). Based on these, we aimed to clarify the respective and combined contributions of structural and topographic factors to rainfall-induced tree destruction. Key findings revealed that when considered in isolation, greater tree height, crown diameter, crown area, leaf area index (LAI), and canopy cover suppressed tree destruction, whereas higher gap fractions increased the probability of tree destruction. However, the synergistic increases of tree structural factors (tree height, crown diameter, and crown area) and forest structural factors (LAI and canopy cover) significantly promoted tree destruction, which can counteract the inhibitory effect of terrain on destruction. In addition, increases in tree structure or canopy density (LAI and canopy cover) also increased the probability of tree destruction at the same elevation. Our findings challenge conventional assumptions in forest management by demonstrating the interaction of tree structure and canopy density can significantly promote tree destruction during heavy rainfall. This highlights the need to avoid overly dense afforestation in vulnerable landscapes and supports more adaptive, climate-resilient restoration strategies.

Malan loess is widely distributed on the Chinese Loess Plateau and poses great challenges to geotechnical, ecological, and agricultural practices due to its unique structure and collapsibility. It is essential to understand the evolution of these properties with depth to assess soil stability and reduce engineering risks in the area. This study investigates the mechanical properties and microstructural evolution of Malan loess with depth and employs multivariate statistical methods to explore their complex interrelationships. Oedometer-collapse tests reveal a 94.2 % reduction in collapsibility coefficient (delta s) from 0.0722 at 1 m to 0.0042 at 9 m, indicating a significant reduction in collapsibility with increasing depth. According to the results of the direct shear test, it showed that the shear strength initially decreases and then increases due to the combined effect of the water content and dry density. Scanning electron microscopy (SEM) images reveal the densification of the loess structure, with changes in particle contact from point to face contact and the evolution from macropores to mesopores and small pores as depth increases. Quantitative analysis by Avzio showed a decrease of 61.5 % in macropores area and an increase of 62.5 % in small pores area. The results obtained by Pearson's correlation analysis and random forest model showed that among these microstructural characteristics, the total pore area (%IncMSE = 22.77 %) is the most important factor influencing the collapsibility properties of loess and water content (%IncMSE = 17.72 %) acts a key role in controlling shear strength. Additionally, compared to traditional methods, the random forest model offers a more insightful understanding of nonlinear relationships and multifactorial coupling effects. These findings provide scientific guidance for geotechnical engineering in loess regions, aiding in risk mitigation and promoting sustainable construction.

The Land Surface Temperature (LST) is well suited to monitor biosphere-atmosphere interactions in forests, as it depends on water availability and atmospheric/meteorological conditions above and below the canopy. Satellite-based LST has proven integral in observing evapotranspiration, estimating surface heat fluxes and characterising vegetation properties. Since the radiative regime of forests is complex, driven by canopy structure, components radiation properties and their arrangement, forest radiative temperatures are subject to strong angular effects. However, this depends on the scale of observation, where scattering mechanisms from canopy-to satellite-scales influence anisotropy with varying orders of magnitude. Given the heterogeneous and complex nature of forests, multi-angular data collection is particularly difficult, necessitating instrumentation distant enough from the canopy to obtain significant canopy brightness temperature and concurrent observations to exclude turbulence/atmospheric effects. Accordingly, current research and understanding on forest anisotropy at varying scales (from local validation level to satellite footprint) remain insufficient to provide practical solutions for addressing angular effects for upcoming thermal satellite sensors and associated validation schemes. This study presents a novel method founded in the optical remote sensing domain to explore the use of microcanopies that represent forests at different scales in the footprint of a multi-angular goniometer observing system. Both Geometric Optical (GO) and volumetric scattering dominated canopies are constructed to simulate impacts of anisotropy in heterogeneous and homogeneous canopies, and observed using a thermal infrared radiometer. Results show that heterogeneous canopies dominated by GO scattering are subject to much higher magnitudes of anisotropy, reaching maximum temperature differences of 3 degrees C off-nadir. Magnitudes of anisotropy are higher in sparse forests, where the gap fraction and crown arrangement (inducing sunlit/shaded portions of soil and vegetation) drive larger off-nadir differences. In dense forests, anisotropy is driven by viewing the maximum portion of sunlit vegetation (hotspot), where the soil is mostly obscured. Canopy structural metrics such as the fractional cover and gap fraction were found to have significant correlation with off-nadir differences. In more homogeneous canopies, anisotropy reaches a lower magnitude with temperature differences up to 1 degrees C, driven largely by volumetric scattering and components radiation properties. Optimal placement of instrumentation at the canopy-scale (more heterogeneous behaviour due to proximity to the canopy and small pixel size) used to validate satellite observations (more homogeneous behaviour due to larger pixel size) was found to be in cases of viewing maximum sunlit vegetation, for dense canopies. Given upcoming high spatial resolution sensors and associated validation schemes needed to benchmark LST and downstream products such as evapotranspiration, a better understanding of anisotropy over forests is critical to provide accurate, long-term and multi-sensor products.

The vadose zone acts as a natural buffer that prevents contaminants such as arsenic (As) from contaminating groundwater resources. Despite its capability to retain As, our previous studies revealed that a substantial amount of As could be remobilized from soil under repeated wet-dry conditions. Overlooking this might underestimate the potential risk of groundwater contamination. This study quantified the remobilization of As in the vadose zone and developed a prediction model based on soil properties. 22 unsaturated soil columns were used to simulate vadose zones with varying soil properties. Repeated wet-dry cycles were conducted upon the As-retaining soil columns. Consequently, 13.9-150.6 mg/kg of As was remobilized from the columns, which corresponds to 37.0-74.6 % of initially retained As. From the experimental results, a machine learning model using a random forest algorithm was established to predict the potential for As remobilization based on readily accessible soil properties, including organic matter (OM) content, iron (Fe) content, uniformity coefficient, D30, and bulk density. Shapley additive explanation analyses revealed the interrelated effects of multiple soil prop-erties. D30, which is inter-related with Fe content, exhibited the highest contribution to As remobilization, fol-lowed by OM content, which was partially mediated by bulk density.

The use of mixed forests and non-native tree species have the potential to mitigate climate change impacts and enhance biodiversity. However, little is known about how forest composition and environmental factors affect each step of natural regeneration in mixed forests, especially in mixtures with non-native trees. Here we investigated how forest composition affected European beech seed survival (through seed tracking), seed sprouting (via field germination experiments), and seedling survival (monthly seedling monitoring) in pure beech forests and in admixtures with Norway spruce and the introduced Douglas-fir in a mast and non-mast year of beech. We also assessed how biotic and abiotic factors (small mammal abundance, ungulate access, seed production, seed burial, canopy cover, distance to nearest adult tree, seedling aggregation, understory density, browsing damage, and soil properties) affected these regeneration dynamics. Seed survival was negatively affected by the presence of conifers and mouse abundance. Seed germination was influenced by whether seeds were buried or not. Seedling survival increased in Douglas-fir admixtures, and in forests with higher soil quality. Browsing damage and ungulate access diminished seedling survival. Seed production had the greatest influence on absolute number of seedlings. Forest composition and environmental factors had distinct impacts on regeneration of beech depending on its ontogenetic stage. Here, we provide evidence supporting the notion that Douglas-fir is not impairing the regeneration of native trees in mixed forests. In fact, mixtures with Douglas-fir benefited the survival of beech seedlings, likely due to better soil properties and less damage from herbivores on these stands.

This study explores the perspectives and adaptive strategies of forest stakeholders across five regions of Europe, North to South-Finland, Lithuania, Romania, Serbia, and Greece-regarding climate change challenges in forestry. 129 stakeholders were surveyed, including forest owners, professionals, environmental NGOs, government representatives, and recreationists, who pointed at soil quality, biodiversity, carbon sequestration, and timber production as the main concerns. Regional threats varied, with storms and pests prevailing in Finland, illegal logging in Lithuania, Romania and Serbia, and fires and unsustainable grazing in Greece. Proposed solutions emphasise active forest management, stakeholder engagement and policy reforms. While Finland and Serbia are optimistic about future forest resilience, Lithuania and Romania are neutral. Greece shows mixed reactions, mainly due to concerns about the political will to implement effective forest policy. The study highlights nuanced regional responses to climate-related forest challenges and the need for region-specific approaches to forest management and policy, with broader implications for environmental governance strategies.

This study investigated seasonal changes in litter and soil organic carbon contents of deciduous and coniferous forests at two altitudes (500 and 1000 m a.s.l.), which were used as proxies for temperature changes. To this aim, adjacent pine (P500 and P1000) and deciduous forests (downy oak forest at 500 m a.s.l. and beech forest at 1000 m a.s.l., D500 and D1000, respectively) were selected within two areas along the western slope of a calcareous massif of the Apennine chain (central Italy). Periodic sampling was carried out within each site (a total of 19 sampling dates: 6 in autumn, 4 in winter and spring, and 5 in summer), taking each time an aliquot of the upper mineral soil horizon and measuring litter thickness and CO2 emission from the soil. The samples were then analyzed for their content of organic C, total N, water-soluble organic C and N (WEOC and WEN, respectively), and the natural abundance of 13C and 15N. Soil and litter C and N stocks were calculated. The chemical and isotopic data suggested that organic C and N transformations from litter to the upper mineral soil horizon were controlled not only by temperature but also by the quality (i.e. C:N ratio) of the plant material. In particular, the more the temperature decreased, the more the quality of the organic matter would influence the process. This was clearly showed by the greater 13C fractionation from litter to soil organic matter (SOM) in D1000 than in P1000, which would indicate a higher degree of transformation under the same thermal condition of the plant residues from the deciduous forest, which were characterized by a more balanced C:N ratio than the pine litter. However, while at 500 m altitude a significant SOM 13C fractionation and a parallel increase in soil CO2 emissions occurred in the warmer seasons, no seasonal delta 13C variation was observed at 1000 m for both forests, despite the different quality of SOM derived from deciduous and coniferous forests. Our findings suggested that organic C and N transformations from litter to the upper soil mineral horizon were greatly controlled by the quality of the plant residues, whereas soil temperature would seem to be the major driver for the seasonal evolution of SOM. This study, by considering two different vegetation types (deciduous and coniferous), allowed to evaluate the combined interactions between the plant residue quality and temperature in controlling litter and SOM mineralisation/accumulation processes.